Data Science at Home
By Francesco Gadaleta
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Category: Technology
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Subscribers: 475
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Episodes: 257
Description
Technology, AI, machine learning and algorithms. Come join the discussion on Discord!
https://discord.gg/4UNKGf3
| Episode | Date |
|---|---|
|
Rust in the Cosmos: Decoding Communication Part I (Ep. 254)
|
Apr 11, 2024 |
|
AI and Video Game Development: Navigating the Future Frontier (Ep. 253)
|
Mar 31, 2024 |
|
Kaggle Kommando's Data Disco: Laughing our Way Through AI Trends (Ep. 252)
|
Mar 07, 2024 |
|
Revolutionizing Robotics: Embracing Low-Code Solutions (Ep. 251)
|
Feb 16, 2024 |
|
Is SQream the fastest big data platform? (Ep. 250)
|
Jan 30, 2024 |
|
OpenAI CEO Shake-up: Decoding December 2023 (Ep. 249)
|
Jan 21, 2024 |
|
Careers, Skills, and the Evolution of AI (Ep. 248)
|
Jan 08, 2024 |
|
Open Source Revolution: AI’s Redemption in Data Science (Ep. 247)
|
Dec 19, 2023 |
|
Money, Cryptocurrencies, and AI: Exploring the Future of Finance with Chris Skinner [RB] (Ep. 246)
|
Dec 11, 2023 |
|
Debunking AGI Hype and Embracing Reality [RB] (Ep. 245)
|
Dec 04, 2023 |
|
Destroy your toaster before it kills you. Drama at OpenAI and other stories (Ep. 244)
|
Dec 01, 2023 |
|
The AI Chip Chat 🤖💻 (Ep. 243)
|
Nov 20, 2023 |
|
Rolling the Dice: Engineering in an Uncertain World (Ep. 242)
|
Nov 09, 2023 |
|
How Language Models Are the Ultimate Database(Ep. 241)
|
Oct 22, 2023 |
|
Elon is right this time: Rust is the language of AI (Ep. 240)
|
Oct 09, 2023 |
|
Attacking LLMs for fun and profit (Ep. 239)
|
Sep 18, 2023 |
|
Unlocking Language Models: The Power of Prompt Engineering (Ep. 238)
|
Sep 11, 2023 |
|
Erosion of Software Architecture Quality in the Age of AI Code Generation (Ep. 237)
|
Aug 30, 2023 |
|
The new dimension of AI: Vector Databases (Ep. 236)
|
Aug 17, 2023 |
|
Building Self Serve Business Intelligence With AI and LLMs at Zenlytic (Ep. 235)
|
Aug 04, 2023 |
|
Money, Cryptocurrencies, and AI: Exploring the Future of Finance with Chris Skinner (Ep. 234)
|
Jul 09, 2023 |
|
Debunking AGI Hype and Embracing Reality (Ep. 233)
|
Jun 26, 2023 |
|
Full steam ahead! Unraveling Forward-Forward Neural Networks (Ep. 232)
|
Jun 15, 2023 |
|
The LLM Battle Begins: Google Bard vs ChatGPT (Ep. 231)
|
Jun 06, 2023 |
|
Unleashing the Force: Blending Neural Networks and Physics for Epic Predictions (Ep. 230)
|
May 30, 2023 |
|
AI’s Impact on Software Engineering: Killing Old Principles? [RB] (Ep. 229)
|
May 25, 2023 |
|
Warning! Mathematical Mayhem Ahead: Demystifying Liquid Time-Constant Networks (Ep. 228)
|
May 16, 2023 |
|
Efficiently Retraining Language Models: How to Level Up Without Breaking the Bank (Ep. 227)
|
May 11, 2023 |
|
Revolutionize Your AI Game: How Running Large Language Models Locally Gives You an Unfair Advantage Over Big Tech Giants (Ep. 226)
|
May 03, 2023 |
|
Rust: A Journey to High-Performance and Confidence in Code at Amethix Technologies (Ep. 225)
|
Apr 26, 2023 |
|
The Power of Graph Neural Networks: Understanding the Future of AI - Part 2/2 (Ep.224)
|
Apr 18, 2023 |
|
The Power of Graph Neural Networks: Understanding the Future of AI - Part 1/2 (Ep.223)
|
Apr 11, 2023 |
|
Leveling Up AI: Reinforcement Learning with Human Feedback (Ep. 222)
|
Apr 04, 2023 |
|
The promise and pitfalls of GPT-4 (Ep. 221)
|
Mar 30, 2023 |
|
AI’s Impact on Software Engineering: Killing Old Principles? (Ep. 220)
|
Mar 14, 2023 |
|
Edge AI applications for military and space [RB] (Ep. 219)
|
Mar 09, 2023 |
|
Prove It Without Revealing It: Exploring the Power of Zero-Knowledge Proofs in Data Science (Ep. 218)
|
Feb 27, 2023 |
|
Deep learning vs tabular models (Ep. 217)
|
Feb 21, 2023 |
|
[RB] Online learning is better than batch, right? Wrong! (Ep. 216)
|
Feb 15, 2023 |
|
Chatting with ChatGPT: Pros and Cons of Advanced Language AI (Ep. 215)
|
Jan 26, 2023 |
|
Accelerating Perception Development with Synthetic Data (Ep. 214)
|
Jan 14, 2023 |
|
Edge AI applications for military and space [RB] (Ep. 213)
|
Dec 13, 2022 |
|
From image to 3D model (Ep. 212)
|
Dec 08, 2022 |
|
Machine learning is physics (Ep. 211)
|
Dec 02, 2022 |
|
Autonomous cars cannot drive. Here is why. (Ep. 210)
|
Nov 21, 2022 |
|
Evolution of data platforms (Ep. 209)
|
Nov 08, 2022 |
|
[RB] Is studying AI in academia a waste of time? (Ep. 208)
|
Nov 02, 2022 |
|
Private machine learning done right (Ep. 207)
|
Oct 25, 2022 |
|
Edge AI for applications in military and space (Ep. 206)
|
Oct 15, 2022 |
|
[RB] What are generalist agents and why they can change the AI game (Ep. 205)
|
Oct 05, 2022 |
|
LIDAR, cameras and autonomous vehicles (Ep. 204)
|
Sep 28, 2022 |
|
Predicting Out Of Memory Kill events with Machine Learning (Ep. 203)
|
Sep 20, 2022 |
|
Is studying AI in academia a waste of time? (Ep. 202)
|
Sep 13, 2022 |
|
Zero-Cost Proxies: How to find the best neural network without training (Ep. 201)
|
Sep 07, 2022 |
|
Online learning is better than batch, right? Wrong! (Ep. 200)
|
Jun 13, 2022 |
|
What are generalist agents and why they can change the AI game (Ep. 199)
|
Jun 03, 2022 |
|
Streaming data with ease. With Chip Kent from Deephaven Data Labs (Ep. 198)
|
May 27, 2022 |
|
Learning from data to create personalized experiences with Matt Swalley from Omneky (Ep. 197)
|
May 16, 2022 |
|
State of Artificial Intelligence 2022 (Ep. 196)
|
May 06, 2022 |
|
Improving your AI by finding issues within data pockets (Ep. 195)
|
Apr 21, 2022 |
|
Fake data that looks, feels, and behaves like production.(Ep.194)
|
Apr 13, 2022 |
|
Batteries and AI in Automotive (Ep. 193)
|
Apr 01, 2022 |
|
Collect data at the edge [RB] (Ep. 192)
|
Mar 25, 2022 |
|
Bayesian Machine Learning with Ravin Kumar (Ep. 191)
|
Mar 19, 2022 |
|
What is spatial data science? With Matt Forest from Carto (Ep. 190)
|
Mar 02, 2022 |
|
Connect. Collect. Normalize. Analyze. An interview with the people from Railz AI (Ep. 189)
|
Feb 22, 2022 |
|
History of data science [RB] (Ep. 188)
|
Feb 16, 2022 |
|
Artificial Intelligence and Cloud Automation with Leon Kuperman from Cast.ai (Ep. 187)
|
Feb 08, 2022 |
|
Embedded Machine Learning: Part 5 - Machine Learning Compiler Optimization (Ep. 186)
|
Feb 03, 2022 |
|
Embedded Machine Learning: Part 4 - Machine Learning Compilers (Ep. 185)
|
Jan 25, 2022 |
|
Embedded Machine Learning: Part 3 - Network Quantization (Ep. 184)
|
Jan 20, 2022 |
|
Embedded Machine Learning: Part 2 (Ep. 183)
|
Jan 15, 2022 |
|
Embedded Machine Learning: Part 1 (Ep.182)
|
Jan 10, 2022 |
|
History of Data Science (Ep. 181)
|
Dec 19, 2021 |
|
Capturing Data at the Edge (Ep. 180)
|
Dec 14, 2021 |
|
[RB] Composable Artificial Intelligence (Ep. 179)
|
Dec 07, 2021 |
|
What is a data mesh and why it is relevant (Ep. 178)
|
Nov 30, 2021 |
|
Environmentally friendly AI (Ep. 177)
|
Nov 23, 2021 |
|
Do you fear of AI? Why? (Ep. 176)
|
Nov 16, 2021 |
|
Composable models and artificial general intelligence (Ep. 175)
|
Nov 09, 2021 |
|
Ethics and explainability in AI with Erika Agostinelli from IBM (ep. 174)
|
Nov 02, 2021 |
|
Is neural hash by Apple violating our privacy? (Ep. 173)
|
Oct 26, 2021 |
|
Fighting Climate Change as a Technologist (Ep. 172)
|
Oct 19, 2021 |
|
AI in the Enterprise with IBM Global AI Strategist Mara Pometti (Ep. 171)
|
Oct 11, 2021 |
|
Speaking about data with Mikkel Settnes from Dreamdata.io (Ep. 170)
|
Sep 24, 2021 |
|
Send compute to data with POSH data-aware shell (Ep. 169)
|
Sep 14, 2021 |
|
How are organisations doing with data and AI? (Ep. 168)
|
Sep 07, 2021 |
|
Don't fight! Cooperate. Generative Teaching Networks (Ep. 167)
|
Aug 31, 2021 |
|
CSV sucks. Here is why. (Ep. 166)
|
Aug 24, 2021 |
|
Reinforcement Learning is all you need. Or is it? (Ep. 165)
|
Aug 17, 2021 |
|
What's happening with AI today? (Ep. 164)
|
Aug 11, 2021 |
|
2 effective ways to explain your predictions (Ep. 163)
|
Aug 03, 2021 |
|
The Netflix challenge. Fair or what? (Ep. 162)
|
Jul 22, 2021 |
|
Artificial Intelligence for Blockchains with Jonathan Ward CTO of Fetch AI (Ep. 161)
|
Jul 15, 2021 |
|
Apache Arrow, Ballista and Big Data in Rust with Andy Grove RB (Ep. 160)
|
Jul 08, 2021 |
|
GitHub Copilot: yay or nay? (Ep. 159)
|
Jul 06, 2021 |
|
Pandas vs Rust [RB] (Ep. 158)
|
Jul 01, 2021 |
|
A simple trick for very unbalanced data (Ep. 157)
|
Jun 22, 2021 |
|
Time to take your data back with Tapmydata (Ep. 156)
|
Jun 15, 2021 |
|
True Machine Intelligence just like the human brain (Ep. 155)
|
Jun 04, 2021 |
|
Delivering unstoppable data with Streamr (Ep. 154)
|
May 26, 2021 |
|
MLOps: the good, the bad and the ugly (Ep. 153)
|
May 24, 2021 |
|
MLOps: what is and why it is important Part 2 (Ep. 152)
|
May 19, 2021 |
|
MLOps: what is and why it is important (Ep. 151)
|
May 11, 2021 |
|
Can I get paid for my data? With Mike Andi from Mytiki (Ep. 150)
|
Apr 28, 2021 |
|
Building high-growth data businesses with Lillian Pierson (Ep. 149)
|
Apr 19, 2021 |
|
Learning and training in AI times (Ep. 148)
|
Apr 13, 2021 |
|
You are the product [RB] (Ep. 147)
|
Apr 11, 2021 |
|
Polars: the fastest dataframe crate in Rust - with Ritchie Vink (Ep. 146)
|
Apr 08, 2021 |
|
Apache Arrow, Ballista and Big Data in Rust with Andy Grove (Ep. 145)
|
Mar 26, 2021 |
|
Pandas vs Rust (Ep. 144)
|
Mar 19, 2021 |
|
Concurrent is not parallel - Part 2 (Ep. 143)
|
Mar 13, 2021 |
|
Concurrent is not parallel - Part 1 (Ep. 142)
|
Mar 10, 2021 |
|
Backend technologies for machine learning in production (Ep. 141)
|
Mar 02, 2021 |
|
You are the product (Ep. 140)
|
Feb 22, 2021 |
|
How to reinvent banking and finance with data and technology (Ep. 139)
|
Feb 15, 2021 |
|
What's up with WhatsApp? (Ep. 138)
|
Feb 07, 2021 |
|
Is Rust flexible enough for a flexible data model? (Ep. 137)
|
Feb 01, 2021 |
|
Is Apple M1 good for machine learning? (Ep.136)
|
Jan 25, 2021 |
|
Rust and deep learning with Daniel McKenna (Ep. 135)
|
Jan 18, 2021 |
|
Scaling machine learning with clusters and GPUs (Ep. 134)
|
Dec 31, 2020 |
|
What is data ethics? (Ep. 133)
|
Dec 19, 2020 |
|
A Standard for the Python Array API (Ep. 132)
|
Dec 08, 2020 |
|
What happens to data transfer after Schrems II? (Ep. 131)
|
Dec 04, 2020 |
|
Test-First Machine Learning [RB] (Ep. 130)
|
Dec 01, 2020 |
|
Similarity in Machine Learning (Ep. 129)
|
Nov 24, 2020 |
|
Distill data and train faster, better, cheaper (Ep. 128)
|
Nov 17, 2020 |
|
Machine Learning in Rust: Amadeus with Alec Mocatta [RB] (ep. 127)
|
Nov 11, 2020 |
|
Top-3 ways to put machine learning models into production (Ep. 126)
|
Nov 07, 2020 |
|
Remove noise from data with deep learning (Ep.125)
|
Nov 03, 2020 |
|
What is contrastive learning and why it is so powerful? (Ep. 124)
|
Oct 30, 2020 |
|
Neural search (Ep. 123)
|
Oct 23, 2020 |
|
Let's talk about federated learning (Ep. 122)
|
Oct 18, 2020 |
|
How to test machine learning in production (Ep. 121)
|
Oct 11, 2020 |
|
Why synthetic data cannot boost machine learning (Ep. 120)
|
Sep 26, 2020 |
|
Machine learning in production: best practices [LIVE from twitch.tv] (Ep. 119)
|
Sep 16, 2020 |
|
Testing in machine learning: checking deeplearning models (Ep. 118)
|
Sep 04, 2020 |
|
Testing in machine learning: generating tests and data (Ep. 117)
|
Aug 29, 2020 |
|
Why you care about homomorphic encryption (Ep. 116)
|
Aug 12, 2020 |
|
Test-First machine learning (Ep. 115)
|
Aug 03, 2020 |
|
GPT-3 cannot code (and never will) (Ep. 114)
|
Jul 26, 2020 |
|
Make Stochastic Gradient Descent Fast Again (Ep. 113)
|
Jul 22, 2020 |
|
What data transformation library should I use? Pandas vs Dask vs Ray vs Modin vs Rapids (Ep. 112)
|
Jul 19, 2020 |
|
[RB] It’s cold outside. Let’s speak about AI winter (Ep. 111)
|
Jul 03, 2020 |
|
Rust and machine learning #4: practical tools (Ep. 110)
|
Jun 29, 2020 |
|
Rust and machine learning #3 with Alec Mocatta (Ep. 109)
|
Jun 22, 2020 |
|
Rust and machine learning #2 with Luca Palmieri (Ep. 108)
|
Jun 19, 2020 |
|
Rust and machine learning #1 (Ep. 107)
|
Jun 17, 2020 |
|
Protecting workers with artificial intelligence (with Sandeep Pandya CEO Everguard.ai)(Ep. 106)
|
Jun 15, 2020 |
|
Compressing deep learning models: rewinding (Ep.105)
|
Jun 01, 2020 |
|
Compressing deep learning models: distillation (Ep.104)
|
May 20, 2020 |
|
Pandemics and the risks of collecting data (Ep. 103)
|
May 08, 2020 |
|
Why average can get your predictions very wrong (ep. 102)
|
Apr 19, 2020 |
|
Activate deep learning neurons faster with Dynamic RELU (ep. 101)
|
Apr 01, 2020 |
|
WARNING!! Neural networks can memorize secrets (ep. 100)
|
Mar 23, 2020 |
|
Attacks to machine learning model: inferring ownership of training data (Ep. 99)
|
Mar 14, 2020 |
|
Don't be naive with data anonymization (Ep. 98)
|
Mar 08, 2020 |
|
Why sharing real data is dangerous (Ep. 97)
|
Mar 01, 2020 |
|
Building reproducible machine learning in production (Ep. 96)
|
Feb 22, 2020 |
|
Bridging the gap between data science and data engineering: metrics (Ep. 95)
|
Feb 14, 2020 |
|
A big welcome to Pryml: faster machine learning applications to production (Ep. 94)
|
Feb 07, 2020 |
|
It's cold outside. Let's speak about AI winter (Ep. 93)
|
Dec 31, 2019 |
|
The dark side of AI: bias in the machine (Ep. 92)
|
Dec 28, 2019 |
|
The dark side of AI: metadata and the death of privacy (Ep. 91)
|
Dec 23, 2019 |
|
The dark side of AI: recommend and manipulate (Ep. 90)
|
Dec 11, 2019 |
|
The dark side of AI: social media and the optimization of addiction (Ep. 89)
|
Dec 03, 2019 |
|
More powerful deep learning with transformers (Ep. 84) (Rebroadcast)
|
Nov 27, 2019 |
|
How to improve the stability of training a GAN (Ep. 88)
|
Nov 18, 2019 |
|
What if I train a neural network with random data? (with Stanisław Jastrzębski) (Ep. 87)
|
Nov 12, 2019 |
|
Deeplearning is easier when it is illustrated (with Jon Krohn) (Ep. 86)
|
Nov 05, 2019 |
|
[RB] How to generate very large images with GANs (Ep. 85)
|
Nov 04, 2019 |
|
More powerful deep learning with transformers (Ep. 84)
|
Oct 27, 2019 |
|
[RB] Replicating GPT-2, the most dangerous NLP model (with Aaron Gokaslan) (Ep. 83)
|
Oct 18, 2019 |
|
What is wrong with reinforcement learning? (Ep. 82)
|
Oct 15, 2019 |
|
Have you met Shannon? Conversation with Jimmy Soni and Rob Goodman about one of the greatest minds in history (Ep. 81)
|
Oct 10, 2019 |
|
Attacking machine learning for fun and profit (with the authors of SecML Ep. 80)
|
Oct 01, 2019 |
|
[RB] How to scale AI in your organisation (Ep. 79)
|
Sep 26, 2019 |
|
Replicating GPT-2, the most dangerous NLP model (with Aaron Gokaslan) (Ep. 78)
|
Sep 23, 2019 |
|
Training neural networks faster without GPU [RB] (Ep. 77)
|
Sep 17, 2019 |
|
How to generate very large images with GANs (Ep. 76)
|
Sep 06, 2019 |
|
[RB] Complex video analysis made easy with Videoflow (Ep. 75)
|
Aug 29, 2019 |
|
[RB] Validate neural networks without data with Dr. Charles Martin (Ep. 74)
|
Aug 27, 2019 |
|
How to cluster tabular data with Markov Clustering (Ep. 73)
|
Aug 20, 2019 |
|
Waterfall or Agile? The best methodology for AI and machine learning (Ep. 72)
|
Aug 14, 2019 |
|
Training neural networks faster without GPU (Ep. 71)
|
Aug 06, 2019 |
|
Validate neural networks without data with Dr. Charles Martin (Ep. 70)
|
Jul 23, 2019 |
|
Complex video analysis made easy with Videoflow (Ep. 69)
|
Jul 16, 2019 |
|
Episode 68: AI and the future of banking with Chris Skinner [RB]
|
Jul 09, 2019 |
|
Episode 67: Classic Computer Science Problems in Python
|
Jul 02, 2019 |
|
Episode 66: More intelligent machines with self-supervised learning
|
Jun 25, 2019 |
|
Episode 65: AI knows biology. Or does it?
|
Jun 23, 2019 |
|
Episode 64: Get the best shot at NLP sentiment analysis
|
Jun 14, 2019 |
|
Episode 63: Financial time series and machine learning
|
Jun 04, 2019 |
|
Episode 62: AI and the future of banking with Chris Skinner
|
May 28, 2019 |
|
Episode 61: The 4 best use cases of entropy in machine learning
|
May 21, 2019 |
|
Episode 60: Predicting your mouse click (and a crash course in deeplearning)
|
May 16, 2019 |
|
Episode 59: How to fool a smart camera with deep learning
|
May 07, 2019 |
|
Episode 58: There is physics in deep learning!
|
Apr 30, 2019 |
|
Episode 57: Neural networks with infinite layers
|
Apr 23, 2019 |
|
Episode 56: The graph network
|
Apr 16, 2019 |
|
Episode 55: Beyond deep learning
|
Apr 09, 2019 |
|
Episode 54: Reproducible machine learning
|
Mar 09, 2019 |
|
Episode 53: Estimating uncertainty with neural networks
|
Jan 23, 2019 |
|
Episode 52: why do machine learning models fail? [RB]
|
Jan 17, 2019 |
|
Episode 51: Decentralized machine learning in the data marketplace (part 2)
|
Jan 08, 2019 |
|
Episode 50: Decentralized machine learning in the data marketplace
|
Dec 26, 2018 |
|
Episode 49: The promises of Artificial Intelligence
|
Dec 19, 2018 |
|
Episode 48: Coffee, Machine Learning and Blockchain
|
Oct 21, 2018 |
|
Episode 47: Are you ready for AI winter? [Rebroadcast]
|
Sep 11, 2018 |
|
Episode 46: why do machine learning models fail? (Part 2)
|
Sep 04, 2018 |
|
Episode 45: why do machine learning models fail?
|
Aug 28, 2018 |
|
Episode 44: The predictive power of metadata
|
Aug 21, 2018 |
|
Episode 43: Applied Text Analysis with Python (interview with Rebecca Bilbro)
|
Aug 14, 2018 |
|
Episode 42: Attacking deep learning models (rebroadcast)
|
Aug 07, 2018 |
|
Episode 41: How can deep neural networks reason
|
Jul 31, 2018 |
|
Episode 40: Deep learning and image compression
|
Jul 24, 2018 |
|
Episode 39: What is L1-norm and L2-norm?
|
Jul 19, 2018 |
|
Episode 38: Collective intelligence (Part 2)
|
Jul 17, 2018 |
|
Episode 38: Collective intelligence (Part 1)
|
Jul 12, 2018 |
|
Episode 37: Predicting the weather with deep learning
|
Jul 09, 2018 |
|
Episode 36: The dangers of machine learning and medicine
|
Jul 03, 2018 |
|
Episode 35: Attacking deep learning models
|
Jun 29, 2018 |
|
Episode 34: Get ready for AI winter
|
Jun 22, 2018 |
|
Episode 33: Decentralized Machine Learning and the proof-of-train
|
Jun 11, 2018 |
|
Episode 32: I am back. I have been building fitchain
|
Jun 04, 2018 |
|
Founder Interview – Francesco Gadaleta of Fitchain
|
May 24, 2018 |
|
Episode 31: The End of Privacy
|
Apr 02, 2018 |
|
Episode 30: Neural networks and genetic evolution: an unfeasible approach
|
Nov 21, 2017 |
|
Episode 29: Fail your AI company in 9 steps
|
Nov 11, 2017 |
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Episode 28: Towards Artificial General Intelligence: preliminary talk
|
Nov 04, 2017 |
|
Episode 27: Techstars accelerator and the culture of fireflies
|
Oct 30, 2017 |
|
Episode 26: Deep Learning and Alzheimer
|
Oct 23, 2017 |
|
Episode 25: How to become data scientist [RB]
|
Oct 16, 2017 |
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Episode 24: How to handle imbalanced datasets
|
Oct 09, 2017 |
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Episode 23: Why do ensemble methods work?
|
Oct 03, 2017 |
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Episode 22: Parallelising and distributing Deep Learning
|
Sep 25, 2017 |
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Episode 21: Additional optimisation strategies for deep learning
|
Sep 18, 2017 |
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Episode 20: How to master optimisation in deep learning
|
Aug 28, 2017 |
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Episode 19: How to completely change your data analytics strategy with deep learning
|
Aug 09, 2017 |
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Episode 18: Machines that learn like humans
|
Mar 28, 2017 |
|
Episode 17: Protecting privacy and confidentiality in data and communications
|
Feb 15, 2017 |
|
Episode 16: 2017 Predictions in Data Science
|
Dec 23, 2016 |
|
Episode 15: Statistical analysis of phenomena that smell like chaos
|
Dec 05, 2016 |
|
Episode 14: The minimum required by a data scientist
|
Sep 27, 2016 |
|
Episode 13: Data Science and Fraud Detection at iZettle
|
Sep 06, 2016 |
|
Episode 12: EU Regulations and the rise of Data Hijackers
|
Jul 26, 2016 |
|
Episode 11: Representative Subsets For Big Data Learning
|
May 03, 2016 |
|
Episode 10: History and applications of Deep Learning
|
Mar 14, 2016 |
|
Episode 9: Markov Chain Montecarlo with full conditionals
|
Mar 02, 2016 |
|
Episode 7: 30 min with data scientist Sebastian Raschka
|
Feb 15, 2016 |
|
Episode 8: Frequentists and Bayesians
|
Feb 15, 2016 |
|
Episode 6: How to be data scientist
|
Jan 19, 2016 |
|
Episode 5: Development and Testing Practices in Data Science
|
Jan 13, 2016 |
|
Episode 1: Predictions in Data Science for 2016
|
Dec 21, 2015 |
|
Episode 2: Networks and Graph Databases
|
Jul 23, 2015 |
|
Episode 4: BigData on your desk
|
Jul 23, 2015 |
|
Episode 3: Data Science and Bio-Inspired Algorithms
|
Jul 08, 2015 |